Bibliographic record
Abstract
The goals of the second volume of the AHDR – Arctic Human Development Report: Regional Processes and Global Linkages – are to provide an update to the first AHDR (2004) in terms of an assessment of the state of Arctic human development; to highlight the major trends and changes unfolding related to the various issues and thematic areas of human development in the Arctic over the past decade; and, based on this assessment, to identify policy relevant conclusions and key gaps in knowledge, new and emerging Arctic success stories. The production of AHDR-II on the tenth anniversary of the first AHDR makes it possible to move beyond the baseline assessment to make valuable comparisons and contrasts across a decade of persistent and rapid change in the North. It addresses critical issues and emerging challenges in Arctic living conditions, quality of life in the North, global change impacts and adaptation, and Indigenous livelihoods. The assessment contributes to our understanding of the interplay and consequences of physical and social change processes affecting Arctic residents’ quality of life, at both the regional and global scales. It shows that the Arctic is not a homogenous region. Impacts of globalization and environmental change differ within and between regions, between Indigenous and non-Indigenous northerners, between genders and along other axes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".